Image Processing Reference
4.3 Per-Tooth Separation Using Min-Cut
FIGURE 8 Segmentation applying the Min-Cut. (a) Selection of the interest point. (b) Seg-
mentation of the selected tooth.
Min-Cut requires human interaction in order to set some important parameters such as the
radius. For this reason, we designed a variant of the methodology used by Tamayo-Quintero
and Gómez-Mendoza [ 19 ] to search the virtual nodes automatically—landmarks—i.e., a point
in the centers of each object—in the ideal case—in this case each tooth, by means of NARF.
The input parameters are shown in Table 2 .
Input Parameters for Min-Cut Segmentation
Interest Point ( x , y , z ) σ SmoothCost Radius
4.4 Semi-Automatic Segmentation (Hybrid Technique)
criteria are mentioned in the previous techniques and the input parameter are shown in Table
FIGURE 9 Semi-automatic segmentation proposal.
Input Parameters Used in the Proposed Methodology
c th θ th σ SC Radius ag
0.5 0.6 15
In Figure 9 , we designed a variant and this methodology is based in the hybridization of
three algorithms: Region Growing, NARF, and Min-Cut. The first step is separated the gum
from teeth using the region growing method then apply NARF and subsequently, each land-
mark is used as source in order to apply the Min-Cut. Finally, the segmentation is composed